Bayesian Optimization of Semicontinuous Carbonation Process Operation Recipe

Abstract

We develop a pilot-scale semicontinuous aqueous mineral carbonation process that captures 40 tons of CO2 per day by combining a 20 wt % aqueous Ca(OH)(2) solution with flue gas containing 15 vol % CO2. From the pilot-plant operation recipe (the so-called "base case"), we propose two new operation recipes to minimize the quantity of reactant used (Lt) and maximize the replenishment period (Pr): a sequence including both a continuous and discrete flow (the so-called "continuous case") and one involving additional reactant replenishment (the so-called "buffer case"). A multiobjective Bayesian optimization was adopted to optimize the operation recipe and minimize the number of simulations. Compared to the base case, the two proposed recipes were found to prolong the Pr by factors of similar to 12 and similar to 2.4 with increases in Lt of similar to 4.6 and similar to 2.6%, respectively. We anticipate that the two proposed recipes will provide operational flexibility by extending the boundaries.